European Journal of Wood and Wood Products最新文献

Surface roughness of heat-treated and sanded wood is a crucial quality indicator in the furniture and woodworking industries. Predicting surface roughness in advance can reduce costs, improve production efficiency, and ensure better compatibility with subsequent material and coating applications, thereby improving overall quality and consistency while supporting more sustainable production. In this study, Siberian pine wood was heat-treated at different temperatures and subsequently sanded on a belt sander using various grit sizes. Taguchi design and Response Surface Methodology (RSM) were first employed to identify and quantify the significance of process parameters affecting surface roughness. Based on these results, several machine learning-based models, including Decision Tree (DT), Gaussian Process Regression (GPR), Multilayer Perceptron (MLP), Random Forest (RF), and Support Vector Machine (SVM), together with RSM, were developed to predict the roughness values of heat-treated and sanded wood. Heat treatment temperature, sandpaper grit size, and grain direction were considered as input variables for the prediction of Ra and Rz surface roughness parameters. Taguchi and RSM analyses revealed that all three factors have a statistically significant effect on surface roughness. Among the tested models, GPR achieved the highest prediction accuracy and was identified as the most suitable approach for modelling the roughness performance of sanded, heat-treated wood surfaces.

This paper investigates the potential of wood stabilisation techniques in improving the mechanical and acoustical properties of temperate wood species to make them suitable for musical instrument making. Many instruments or parts are usually made with tropical woods, specifically woodwind instruments and fingerboards of chordophones. For these applications, the wood must be stable, with low porosity and good machinability. The increasingly strict regulations on international trade of vulnerable species reduce the availability of such species. Therefore, a wood stabilisation process using methyl methacrylate impregnation is proposed, focusing on these specific domain criteria. This aims to achieve properties approaching those of African blackwood (Dalbergia melanoxylon) used for clarinet and oboes, and African ebony (Diospyros crassiflora) used for chordophones fingerboards. Ten different temperate wood species and six specimens (tubes) per species were tested with this process. The Shore-D hardness, hygroscopic behaviour of wood through roundness, moisture exclusion efficiency and anti-swelling efficiency, the acoustic loss factor of the cavity and the density of samples were compared before and after stabilisation. The results suggest that hornbeam (Carpinus betulus), maple (Acer spp.) and beech (Fagus sylvatica) can be used as stabilised materials, for several applications, with improved properties. Generally, the density and hardness are significantly improved and acoustic loss factors and swelling are reduced, to reach values suitable for instrument making, whilst not reaching absolute values of tropical reference woods.

For the natural fiber-reinforced composite materials, such as the recombinant bamboo obvious creep behavior is usually observed. In this paper, the compressive creep property of the material was chosen as the research subject. First the standard compressive fracture experiment was carried out to provide the basic stress level parameters for the compressive creep test. Then the creep experiment under four different stress levels was conducted to record the strain evolution process. Finally the creep property was analyzed based on different selected models and the stress level effect. The results showed that the stress level affects the creep property obviously. The creep strain growth speed under higher stress levels is much quicker than that under lower stress levels. In addition, compared with the traditional Burgers model, the combination of the variable-order fractional derivative defined Maxwell model and the stress level defined model parameters can provide excellent performance in fitting the strain evolution process during the whole experiment period, which makes it worth popularizing and utilizing in actual engineering.

Recently, utilization of Wood Plastic Composite (WPC) panels has grown in both indoor and outdoor settings. Drilling these panels are essential for installation, assembly, and securing components productivity. This study focuses on developing predictive modeling and optimization for drilling WPC composite panels by considering the machining parameters, mean roughness depth (R_z), and average surface roughness (R_a). An experimental design based on an L₂₇ orthogonal array is employed, along with regression and Artificial Neuro-Fuzzy Inference System (ANFIS) approaches to enhance prediction accuracy for R_a and R_z. Also, the key input parameters have included diameter of drill bit (d), feed rate (f), and spindle speed (N). The results have indicated that R_a and R_z are mainly influenced by f and d, which increase the roughness owing to enhanced cutting forces and poor chip evacuation. Conversely, higher N and lower f reduce the R_a and R_z. Optimized parameters identified through desirability-based methods are N = 3000 rpm, f = 75 mm/min, and d = 6 mm. Results showed that ANFIS prediction models outperform response surface methodology (RSM) models with higher R² values of 0.9525 and 0.9581 for R_a and R_z with root mean squared error value of 0.87 and 2.52 (R_a and R_z) that are lower than RSM models. This study introduces the ANFIS model approach integrated with particle swarm optimization (PSO) and hippopotamus optimization algorithm (HOA), to enhance the performance of the drilling of WPC. This enables more accurate and reliable optimization of R_a and R_z compared to previous single or non-hybrid algorithm approaches.

This study explores the optimal loading and processing parameters for incorporating nano-zinc oxide (nano-ZnO) into urea–formaldehyde (UF) resin to fabricate enhanced medium density fibreboards (MDFs). Enhanced MDF panels would in turn address challenges such as moisture sensitivity, biological durability, and formaldehyde content. Nano-ZnO was added at three loadings (1%, 2%, and 3%) and sonicated for 5, 10, and 15 min to optimize dispersion quality and evaluate the structure–property relationship. MDFs prepared with these formulations were tested for physical, mechanical, mycological properties, and formaldehyde content. Nano-ZnO loaded UF resin dispersions were characterised using SEM and XRD and showed well-dispersed formulations. Incorporation of nano-ZnO improved dimensional stability and strength, reduced fungal spread, and lowered the formaldehyde emission by up to 73%. These improvements are attributed to enhanced resin cross-linking and uniform nanoparticle dispersion, which reduced hydrophilicity and increased bonding efficiency. The 1% nano-ZnO formulation showed the highest mechanical improvement, while 3% provided the best antifungal performance. The study demonstrates that controlled sonication and optimal nano-ZnO loading can significantly enhance the performance and sustainability of MDF panels.

In this study, Eucalyptus urophylla × grandis particles were used as the raw materials and poly-4,4′-diphenylmethane diisocyanate (pMDI) served as the adhesive. A two-way experimental design was employed to systematically investigate the combined effects of particle moisture content (PMC, 3%, 6%, 9%, and 12%) and resin content (RC, 3%, 6%, and 9%) on the physical and mechanical properties of particleboard. Fluorescence microscopy and digital image correlation (DIC) were integrated to elucidate the structure-property relationships between bonding interface characteristics and board-level mechanical behavior. The results showed that a balanced combination of PMC and RC markedly improved the bonding quality and overall performance of particleboard. Optimal performance was achieved at 9% PMC and 3% RC, where all mechanical and dimensional stability indicators met the GB/T 4897 − 2015 P2 type standard. Fluorescence microscopy revealed that moderate increase in PMC and RC enhanced adhesive dispersion and promoted the formation of a continuous three-dimensional bonding network at the particle interface. DIC analysis further indicated that optimized bonding conditions led to more homogeneous strain distribution and reduced localized shear concentration during bending. These findings provide fundamental insights into the interfacial mechanisms governing pMDI-bonded particleboard performance and offer valuable guidance for the design and production of high-performance, moisture-adaptive particleboard.

Wood scrimber is an innovative wood product that offers a viable solution to the shortage of large-sized wood required for structural applications. This study provides comprehensive methodologies for the numerical modelling of structural-scale beams made of scrimber. Initially, a constitutive law based on continuum damage mechanics was developed for this product, integrated into ABAQUS/Explicit as a user-defined subroutine (VUMAT). It was found that the explicit subroutine could accurately capture failure modes, avoid convergence problems, and eliminate the need for specifying mesh-size dependent fracture energy. Subsequently, a calibration approach was proposed for the non-standard specimens to transform material parameters from experimental data to simulation data, addressing the errors between macroscopic specimens and microscopic elements caused by buckling and uneven stress distribution. Furthermore, to model the bending behaviour of a structural-scale scrimber beam, a strategy was proposed to account for the size effect. The results demonstrate that the size effect resulted in a 12.5% reduction in load capacity. The numerical result accounting for the size effect significantly improved agreement with the test data, reducing the maximum error in the ultimate load from 9.8% to 2.5%.

The higher heating value (HHV) and the immediate, final as well as chemical analyses ofdebarked wood for thirty-eight species from the central-western region of Cuba were studied. A new model to compute the HHV based on the elemental composition for all species and for each of the thirty-eight species was proposed. The proposed model for HHV calculation was compared with other available correlations, finding a better fit for the proposal, with a mean deviation of (:pm:2%) and (:pm:4%) in 83.8% and 95.4% of the available experimental data. The best individual fit was obtained for Spondias mombin, L. with a mean error of (:pm:2%) and (:pm:4%) in 89.6% and 98.3% of the available data, respectively, while the weaker fit was computed for Cordia gerascanthoides, H. B. K. with a mean deviation of (:pm:2%) and (:pm:4%) in 80.7% and 90.2% of the available data, respectively. The results show that the model presented in this work is satisfactory, with statistical tests confirming an (:{:text{R}}^{2}>0.9). In all cases, the agreement of the proposed method is good enough to be considered satisfactory for practical design. Given the lack of equal precedents in the literature, this work is considered a contribution to the field of knowledge for the Caribbean region.

This study was to evaluate the feasibility of producing long strands of conventional sizes from post-consumer wood and to assess the impact on the properties of strand boards containing a fraction of such recycled strands. Randomly oriented strand boards were made using varying proportions of recycled wood (0%, 10%, 30%, 50% and 100%) mixed with virgin wood strands. To determine the influence of recycled wood on board properties, we analysed the fractional composition of strands, their wettability, sorption kinetics and cellulose crystallinity for both virgin and recycled wood, and tested various physical and mechanical properties of the resulting strand boards. We then compared the performance of these boards with the requirements of the European standard EN 300 and data from other studies. Boards containing recycled wood exhibited slightly lower but not statistically significant average values for modulus of rupture (MOR) and modulus of elasticity (MOE) compared with the control made from virgin wood. However, the results for internal bond (IB) strength indicated strong adhesion of the recycled strands, attributed to their favourable wetting behaviour. A key benefit of incorporating recycled wood was a significant improvement in the dimensional stability of the boards. In particular, boards made entirely of recycled strands demonstrated a 49.6% reduction in thickness swelling after 24 h of water immersion compared to those made exclusively from virgin wood. The findings indicate that substituting virgin strands with recycled counterparts enables the production of OSB/3 panels using shorter, narrower and thicker strands than standard virgin wood strands.

The sustainable utilization of wood waste is critical for reducing environmental impact and promoting more resource-efficient construction materials. This study investigates the effects of wood flour particle size, wood content, and extrusion parameters—specifically extrusion rate—on the fabrication of wood flour–epoxy composites designed for extrusion-based 3D printing. Through a factorial experimental design, the effects of these parameters on mechanical, physical, and fire-resistant properties were systematically evaluated. Characterization included flexural and compressive strength tests, water absorption, dimensional stability, and fire resistance assessments. Statistical analyses revealed that the epoxy-to-wood ratio is the most influential factor, with a 55:45 ratio yielding optimal results enhanced mechanical strength, improved dimensional stability, and superior fire resistance, while minimizing surface defects. These findings highlight the importance of precise extrusion parameter optimization to produce high-performance composites that incorporate renewable wood resources. The results provide valuable insights for developing partially bio-based materials capable of reducing reliance on petroleum-derived polymers, supporting improved sustainability and performance in construction applications.